A sensor device for sensing biological or clinical data may communicate data with other similar sensor devices. Such data may be used for management of healthcare. However, several challenges exist for the collection, fusion, interpretation, and sharing of the data with appropriate privacy and security. There can be a great deal of information from such networks and thus, healthcare providers, such as physicians or nurses, may become overwhelmed by the volume of data received. In addition, data from patients may not have an adequate level of reliability. For example, if data is improperly collected, the data may be corrupted or inaccurate. Also, patient data may be sensitive such that it may be desired that certain types of data be kept private. These problems may be encountered in non-healthcare settings as well such as in any situation in which large amounts of information can overwhelm a user.
Often only certain portions of the voluminous information received pertains to a critical condition or event in which action must be taken immediately. In a healthcare setting, other portions of the data may describe only routine conditions in which care need not be administered on a critical basis. Still other portions of the data may describe normal conditions in which no care is necessary at all. However, with the abundance of information being reported through sensor devices in the network, critical data may often become masked by other less critical data.
In one example, sensing the blood glucose of a diabetic patient may produce a large number of blood glucose readings per day. When multiple diabetic patients are each producing a similar number of readings per day and the system presents all of this data to a healthcare provider or monitoring facility, there is a substantial risk that a manual review of data might result in missing an abnormal reading embedded among the numerous readings within normal range. This problem is compounded when numerous readings of different parameters for different conditions among multiple patients are all received via a healthcare sensor network.
Therefore, there is a need to collect data via a sensor network in an efficient manner in which critical data may be effectively identified. There is also a need to identify and prioritize data such that data of higher importance may be identified and acted upon in an expeditious manner while data of lower importance may also be acted upon in a manner consistent with its level of importance.